all-in-one-audio
Maintainer: erickluis00
4
| Property | Value |
|---|---|
| Run this model | Run on Replicate |
| API spec | View on Replicate |
| Github link | View on Github |
| Paper link | No paper link provided |
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Model overview
The all-in-one-audio model is an AI-powered music analysis and stem separation tool created by erickluis00. It combines the capabilities of the Demucs and MDX-Net models to provide a comprehensive audio processing solution. The model can analyze music structure, separate audio into individual stems (such as vocals, drums, and bass), and generate sonifications and visualizations of the audio data. It is similar to other audio separation models like demucs and spleeter, but offers a more all-in-one approach.
Model inputs and outputs
The all-in-one-audio model takes a music input file and several optional parameters to control the analysis and separation process. The outputs include the separated audio stems, as well as sonifications and visualizations of the audio data.
Inputs
- music_input: An audio file to be analyzed and processed.
- sonify: A boolean flag to save sonifications of the analysis results.
- visualize: A boolean flag to save visualizations of the analysis results.
- audioSeparator: A boolean flag to enable audio separation using the MDX-net model.
- include_embeddings: A boolean flag to include audio embeddings in the analysis results.
- include_activations: A boolean flag to include activations in the analysis results.
- audioSeparatorModel: The name of the pre-trained model to use for audio separation.
Outputs
- mdx_other: An array of URIs for the separated "other" stems (such as instruments) using the MDX-net model.
- mdx_vocals: A URI for the separated vocal stem using the MDX-net model.
- demucs_bass: A URI for the separated bass stem using the Demucs model.
- demucs_drums: A URI for the separated drum stem using the Demucs model.
- demucs_other: A URI for the separated "other" stem using the Demucs model.
- demucs_piano: A URI for the separated piano stem using the Demucs model.
- sonification: A URI for the generated sonification of the analysis results.
- demucs_guitar: A URI for the separated guitar stem using the Demucs model.
- demucs_vocals: A URI for the separated vocal stem using the Demucs model.
- visualization: A URI for the generated visualization of the analysis results.
- analyzer_result: A URI for the overall analysis results.
- mdx_instrumental: A URI for the separated instrumental stem using the MDX-net model.
Capabilities
The all-in-one-audio model can analyze the structure of music and separate the audio into individual stems, such as vocals, drums, and instruments. It uses the Demucs and MDX-Net models to achieve this, combining their strengths to provide a comprehensive audio processing solution.
What can I use it for?
The all-in-one-audio model can be used for a variety of music-related applications, such as audio editing, music production, and music analysis. It can be particularly useful for producers, musicians, and researchers who need to work with individual audio stems or analyze the structure of music. For example, you could use the model to separate the vocals from a song, create remixes or mashups, or study the relationships between different musical elements.
Things to try
Some interesting things to try with the all-in-one-audio model include:
- Experimenting with the different audio separation models (Demucs and MDX-Net) to see which one works best for your specific use case.
- Generating sonifications and visualizations of the audio data to gain new insights into the music.
- Combining the separated audio stems in creative ways to produce new musical compositions.
- Analyzing the structure of music to better understand the relationships between different musical elements.
This summary was produced with help from an AI and may contain inaccuracies - check out the links to read the original source documents!
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